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      Computer Simulation of Magnetic Resonance Angiography Imaging: Model Description and Validation

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          Abstract

          With the development of medical imaging modalities and image processing algorithms, there arises a need for methods of their comprehensive quantitative evaluation. In particular, this concerns the algorithms for vessel tracking and segmentation in magnetic resonance angiography images. The problem can be approached by using synthetic images, where true geometry of vessels is known. This paper presents a framework for computer modeling of MRA imaging and the results of its validation. A new model incorporates blood flow simulation within MR signal computation kernel. The proposed solution is unique, especially with respect to the interface between flow and image formation processes. Furthermore it utilizes the concept of particle tracing. The particles reflect the flow of fluid they are immersed in and they are assigned magnetization vectors with temporal evolution controlled by MR physics. Such an approach ensures flexibility as the designed simulator is able to reconstruct flow profiles of any type. The proposed model is validated in a series of experiments with physical and digital flow phantoms. The synthesized 3D images contain various features (including artifacts) characteristic for the time-of-flight protocol and exhibit remarkable correlation with the data acquired in a real MR scanner. The obtained results support the primary goal of the conducted research, i.e. establishing a reference technique for a quantified validation of MR angiography image processing algorithms.

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          Wavelet-based Rician noise removal for magnetic resonance imaging.

          R.D. Nowak (1999)
          It is well known that magnetic resonance magnitude image data obey a Rician distribution. Unlike additive Gaussian noise, Rician "noise" is signal-dependent, and separating signal from noise is a difficult task. Rician noise is especially problematic in low signal-to-noise ratio (SNR) regimes where it not only causes random fluctuations, but also introduces a signal-dependent bias to the data that reduces image contrast. This paper studies wavelet-domain filtering methods for Rician noise removal. We present a novel wavelet-domain filter that adapts to variations in both the signal and the noise.
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            Robust Rician noise estimation for MR images.

            In this paper, a new object-based method to estimate noise in magnitude MR images is proposed. The main advantage of this object-based method is its robustness to background artefacts such as ghosting. The proposed method is based on the adaptation of the Median Absolute Deviation (MAD) estimator in the wavelet domain for Rician noise. The MAD is a robust and efficient estimator initially proposed to estimate Gaussian noise. In this work, the adaptation of MAD operator for Rician noise is performed by using only the wavelet coefficients corresponding to the object and by correcting the estimation with an iterative scheme based on the SNR of the image. During the evaluation, a comparison of the proposed method with several state-of-the-art methods is performed. A quantitative validation on synthetic phantom with and without artefacts is presented. A new validation framework is proposed to perform quantitative validation on real data. The impact of the accuracy of noise estimation on the performance of a denoising filter is also studied. The results obtained on synthetic images show the accuracy and the robustness of the proposed method. Within the validation on real data, the proposed method obtained very competitive results compared to the methods under study. Copyright 2010 Elsevier B.V. All rights reserved.
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              High-performance computing MRI simulations.

              A new open-source software project is presented, JEMRIS, the Jülich Extensible MRI Simulator, which provides an MRI sequence development and simulation environment for the MRI community. The development was driven by the desire to achieve generality of simulated three-dimensional MRI experiments reflecting modern MRI systems hardware. The accompanying computational burden is overcome by means of parallel computing. Many aspects are covered that have not hitherto been simultaneously investigated in general MRI simulations such as parallel transmit and receive, important off-resonance effects, nonlinear gradients, and arbitrary spatiotemporal parameter variations at different levels. The latter can be used to simulate various types of motion, for instance. The JEMRIS user interface is very simple to use, but nevertheless it presents few limitations. MRI sequences with arbitrary waveforms and complex interdependent modules are modeled in a graphical user interface-based environment requiring no further programming. This manuscript describes the concepts, methods, and performance of the software. Examples of novel simulation results in active fields of MRI research are given. (c) 2010 Wiley-Liss, Inc.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2014
                16 April 2014
                : 9
                : 4
                : e93689
                Affiliations
                [1]Medical Electronics Division, Institute of Electronics, Lodz University of Technology, Lodz, Poland
                Universidad de Castilla-La Mancha, Spain
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Conceived and designed the experiments: AK AM. Performed the experiments: AK GD MS. Analyzed the data: AK. Contributed reagents/materials/analysis tools: AK PS AM. Wrote the paper: AK. Designed the softwate tools used in the study: AK PS. Arranged experiments with the real MR scanner: MS. Performed flow simulation in the COMSOL software: AK GD. Designed the experiment with the physical phantoms: AM. Overall research coordination and management: AK.

                Article
                PONE-D-13-49923
                10.1371/journal.pone.0093689
                3989177
                24740285
                c7edf0f7-e93e-4c7c-9d02-38dc053e6b95
                Copyright @ 2014

                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 26 November 2013
                : 8 March 2014
                Page count
                Pages: 15
                Funding
                This paper was supported by the Polish National Science Centre under grants no. N N519 650940 and 2013/08/M/ST7/00943. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology and Life Sciences
                Biotechnology
                Bioengineering
                Biomedical Engineering
                Computer and Information Sciences
                Computer Modeling
                Engineering and Technology
                Aerospace Engineering
                Avionics
                Synthetic Vision Systems
                Signal Processing
                Image Processing
                Signal Filtering
                Medicine and Health Sciences
                Medical Physics
                Radiology and Imaging
                Physical Sciences
                Mathematics
                Applied Mathematics
                Algorithms

                Uncategorized
                Uncategorized

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